Hi dear Mi³ego dnia, I am sorry I got lost here. May be it it sound if I write you about what I am going to do.
"To test such null hypotheses we used the Monte Carlo test, i.e. we chose randomly (5000 times) a value for the current dependent characteristic (richness or actual species pool) in the interval 0 to the maximum possible value of the dependent variable for each observed value of the current independent variable. The maximum observed value was either the calculated size of the regional pool, or the measured size of the actual pool. Each time, we calculated the correlation coefficient r between the independent and dependent variables in order to achieve the empirical distribution of r for the null hypothesis conditions. The empirical probability of cases with a correlation between the two studied variables positive and stronger than that observed in the real data, served as an estimate of the significance level for rejecting the null hypotheses. Thus, by saying that there exists a significant relationship, we mean that the relationship is significantly stronger than expected from our null model". I hope I can get all necessary R code for analyses. Chitra -- View this message in context: http://r.789695.n4.nabble.com/Please-help-me-about-Monte-Carlo-Permutation-tp3017131p3019329.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
